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A novel deep learning based hippocampus subfield segmentation method

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A novel deep learning based hippocampus subfield segmentation method

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dc.contributor.author Manjón Herrera, José Vicente es_ES
dc.contributor.author Romero, José E. es_ES
dc.contributor.author Coupe, Pierrick es_ES
dc.date.accessioned 2023-06-23T18:02:08Z
dc.date.available 2023-06-23T18:02:08Z
dc.date.issued 2022-01-25 es_ES
dc.identifier.issn 2045-2322 es_ES
dc.identifier.uri http://hdl.handle.net/10251/194517
dc.description.abstract [EN] The automatic assessment of hippocampus volume is an important tool in the study of several neurodegenerative diseases such as Alzheimer's disease. Specifically, the measurement of hippocampus subfields properties is of great interest since it can show earlier pathological changes in the brain. However, segmentation of these subfields is very difficult due to their complex structure and for the need of high-resolution magnetic resonance images manually labeled. In this work, we present a novel pipeline for automatic hippocampus subfield segmentation based on a deeply supervised convolutional neural network. Results of the proposed method are shown for two available hippocampus subfield delineation protocols. The method has been compared to other state-of-the-art methods showing improved results in terms of accuracy and execution time. es_ES
dc.description.sponsorship This research was supported by the Spanish DPI2017-87743-R grant from the Ministerio de Economia, Industria y Competitividad of Spain. This study has been also carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project) and Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57). The authors gratefully acknowledge the support of NVIDIA Corporation with their donation of the TITAN X GPU used in this research. es_ES
dc.language Inglés es_ES
dc.publisher Nature Publishing Group es_ES
dc.relation.ispartof Scientific Reports es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject MRI es_ES
dc.subject Hipocampus es_ES
dc.subject Segmentation es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title A novel deep learning based hippocampus subfield segmentation method es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1038/s41598-022-05287-8 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-87743-R/ES/DESARROLLO DE UNA PLATAFORMA ONLINE PARA EL ANALISIS ANATOMICO DEL CEREBRO TOLERANTE A LA PRESENCIA DE ALTERACIONES PATOLOGICAS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ANR//ANR-10-IDEX-03-02/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ANR//ANR-10-LABX-57/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Manjón Herrera, JV.; Romero, JE.; Coupe, P. (2022). A novel deep learning based hippocampus subfield segmentation method. Scientific Reports. 12(1):1-9. https://doi.org/10.1038/s41598-022-05287-8 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1038/s41598-022-05287-8 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 9 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 1 es_ES
dc.identifier.pmid 35079061 es_ES
dc.identifier.pmcid PMC8789929 es_ES
dc.relation.pasarela S\484085 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Agence Nationale de la Recherche, Francia es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
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upv.costeAPC 2166 es_ES


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